Papers
2
Total Citations
33
H-Index
2
About
Jin Qi is an emerging researcher specializing in bioelectrical signal processing, human-machine interfaces, and assistive robotics. His work sits at the intersection of electromyography (EMG) technology, machine learning, and rehabilitation engineering, with a focus on enabling intuitive volitional control of robotic and exoskeletal devices for individuals with motor impairments. Qi's most notable contribution, "Volitional Control of Upper-Limb Exoskeleton Empowered by EMG Sensors and Machine Learning Computing" (2023), has accumulated 23 citations and addresses one of the field's most persistent challenges: reliably decoding multi-channel bioelectrical signals in the presence of noise, motion artifacts, and individual biological variability. By leveraging emerging machine learning frameworks, his research offers a meaningful step forward in making bionic assistive robots more responsive and user-adaptive. His complementary 2022 study on real-time, fixed-bandwidth frequency-domain EMG processing for robotic hands — garnering 10 citations — demonstrates his commitment to practical, embedded system solutions that move beyond conventional RMS-based algorithms to improve real-world performance. Together, these works position Qi as a promising contributor to the future of intelligent prosthetics and exoskeleton-assisted rehabilitation.
Research Focus
Key Achievements
Top Papers
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